arXiv:2409.00089cs.CRcs.AI2024-09综述被引 37

系统梳理大模型水印技术,为版权保护和内容溯源提供指南

Watermarking Techniques for Large Language Models: A Survey

  • 从传统数字水印出发,分析其在大模型中的继承与应用路径
  • 总结现有水印方法的优劣,涵盖文本、图像、音频等多模态场景
  • 适合关注AI版权、内容安全与可信生成的研究者和开发者

随着人工智能技术的快速发展与广泛应用,大型语言模型(LLMs)在生产、创作、学习和工作效率提升中发挥重要作用。然而,其滥用可能引发知识产权纠纷、学术不端、虚假信息及幻觉等问题。已有研究提出使用大模型水印技术实现模型知识产权保护和输出内容的可追溯性。本文是首个对大模型水印技术进行深入调研与分析的综述。文章首先回顾传统数字水印的发展历程,继而系统分析当前大模型水印研究现状,深入探讨各类技术间的传承关系与内在关联。通过剖析这些关联,本文为将传统水印技术迁移至大模型领域提供思路,推动水印技术的跨领域融合与创新。此外,本文评估了各类水印方法的优缺点,并针对大模型向多模态发展的趋势,详细分析了视觉、音频等多模态大模型水印技术,为相关研究提供参考。最后,本文深入探讨了当前水印技术面临的挑战与未来发展方向,为后续大模型水印研究与应用提供重要启示。

原文摘要 · Abstract (English)

With the rapid advancement and extensive application of artificial intelligence technology, large language models (LLMs) are extensively used to enhance production, creativity, learning, and work efficiency across various domains. However, the abuse of LLMs also poses potential harm to human society, such as intellectual property rights issues, academic misconduct, false content, and hallucinations. Relevant research has proposed the use of LLM watermarking to achieve IP protection for LLMs and traceability of multimedia data output by LLMs. To our knowledge, this is the first thorough review that investigates and analyzes LLM watermarking technology in detail. This review begins by recounting the history of traditional watermarking technology, then analyzes the current state of LLM watermarking research, and thoroughly examines the inheritance and relevance of these techniques. By analyzing their inheritance and relevance, this review can provide research with ideas for applying traditional digital watermarking techniques to LLM watermarking, to promote the cross-integration and innovation of watermarking technology. In addition, this review examines the pros and cons of LLM watermarking. Considering the current multimodal development trend of LLMs, it provides a detailed analysis of emerging multimodal LLM watermarking, such as visual and audio data, to offer more reference ideas for relevant research. This review delves into the challenges and future prospects of current watermarking technologies, offering valuable insights for future LLM watermarking research and applications.

大模型水印技术内容溯源多模态

Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品;中文卡片由大模型生成,请以原文为准。